So entfernen Sie die DATUMZEIT mit NAN-Werten

Question

Wie entferne ich DATUM und ZEIT mit dem NAN-Wert in der Spalte 'oo'.

das ist mein csv

DATUM, ZEIT, AUF, HIGH, LOW, ZU, VOLUME 02/03/1997,09: 04: 00,3046.00,3048.50,3046.00,3047.50,505
02 /03/1997,09:05:00,3047,00,3048,00,3046,00,3047,00,162
02/03/1997,09: 06: 00,3047,50,3048,00,3047,00,3047,50,98
02/03/1997 , 09: 07: 00,3047,50,3047,50,3047,00,3047,50,228
02/03/1997,09: 08: 00,3048,00,3048,00,3047,50,3048,00,136
02/03/1997,09: 09 : 00,3048,00,3048,00,3046,50,3046,50,50174
02/03/1997,09: 10: 00,3046.50,3046,50,3045,00,3045,00,134
02/03/1997,09: 11: 00,3045,50,3046,00,3044,00,3045,00,43
02/03 /1997,09:12:00,3045,00,2045,50,3045,00,3045,00,214
02/03/1997,09: 13: 00,3045,50,3045,50,3045,50,3045,50,8
02/03/1997,09 : 14: 00,3045,50,3046,00,3044,50,3044,50,152
02/03/1997,09: 15: 00,3044,00,3044,00,3042,50,3042,50,126
02/03/1997,09: 16: 00 , 3043,50,3043,50,3043,00,3043,00,128
02/03/1997,09: 17: 00,3042,50,3043,50,3042,50,3043,50,23
02/03/1997,09: 18: 00,3043,50,3044,50 , 304 3.00.3044,00,51
02/03/1997,09: 19: 00,3044,50,3044,50,3043,00,3043,00,18
02/03/1997,09: 20: 00,3043,00,3045,00,00,3043,00,3045,00, 23
02/03/1997,09: 21: 00,3045.00,3045.00,3044.50,3045.00,51
02/03/1997,09: 22: 00,3045.00,3045.00,3045.00,3045.00,47
02 /03/1997,09:23:00,3045,00,70
02/03/1997,09: 24: 00,3045,00,3045,00,3045,00,3045,00,131
02/03/1997 , 09: 25: 00,3044,50,3044,50,3043,50,3043,50,138
02/03/1997,09: 26: 00,3043,50,3043,50,3043,50,503043,50,6
02/03/1997,09: 27: 00,3043,00,50
02/03/1997,09: 28: 00,3043,00,3044,00,3043,00,3044,00,32
02/03 /1997,09:29:00,3044.50,3044.50,3044.50,3044.50,63
02/03/1997,09: 30: 00,3045.00,3045.00,3045.00,3045.00,28

hier ist mein Code.

exp = pd.read_csv('example.txt', parse_dates = [["DATE", "TIME"]], index_col=0) 

exp['oo'] = opcl.OPEN.resample("5Min").first() 
print exp['oo'] 

und ich diese

DATE_TIME 
1997-02-03 09:04:00  NaN 
1997-02-03 09:05:00 3047.0 
1997-02-03 09:06:00  NaN 
1997-02-03 09:07:00  NaN 
1997-02-03 09:08:00  NaN 
1997-02-03 09:09:00  NaN 
1997-02-03 09:10:00 3046.5 

I aller DATE_TIME Zeilen loswerden will mit NaN in der 'oo' Spalte Werte annehmen. Ich habe es versucht.

exp['oo'] = exp['oo'].dropna() 

Aber ich bekomme das gleiche. Ich habe alle geworfen warf die http://pandas.pydata.org/pandas-docs/stable/missing_data.html

Und sah auf dieser ganzen Website.

Ich möchte meinen csv-Leser das gleiche aber IDK behalten.

Wenn jemand helfen könnte, wäre es sehr dankbar, danke für Ihre Zeit.

Answer 1

Ich glaube, Sie wollen, dass diese:

>>> exp.OPEN.resample("5Min", how='first') 

DATE_TIME 
1997-02-03 09:00:00 3046.0 
1997-02-03 09:05:00 3047.0 
1997-02-03 09:10:00 3046.5 
1997-02-03 09:15:00 3044.0 
1997-02-03 09:20:00 3043.0 
1997-02-03 09:25:00 3044.5 
1997-02-03 09:30:00 3045.0 
Freq: 5T, Name: OPEN, dtype: float64